Reverse Dependencies of databricks-sdk

The following projects have a declared dependency on databricks-sdk:

• acryl-datahub — A CLI to work with DataHub metadata
• airflow-tools — no summary
• apache-airflow-providers-databricks — Provider package apache-airflow-providers-databricks for Apache Airflow
• bitfount — Machine Learning and Federated Learning Library.
• brickflows — Deploy scalable workflows to databricks using python
• cdpdev-datahub — A CLI to work with DataHub metadata
• chalkpy — Python SDK for Chalk
• composer — Composer is a PyTorch library that enables you to train neural networks faster, at lower cost, and to higher accuracy.
• dagster-databricks — Package for Databricks-specific Dagster framework op and resource components.
• databricks-agents — Mosaic AI Agent Framework SDK
• databricks-ai-bridge — Official Python library for Databricks AI support
• databricks-azure-ad-sync-provider — Default template for PDM package
• databricks-connect — Databricks Connect Client
• databricks-genai — Interact with the Databricks Generative AI APIs in python
• databricks-genai-inference — Interact with the Databricks Foundation Model API from python
• databricks-labs-blueprint — Common libraries for Databricks Labs
• databricks-labs-lsql — Lightweight stateless SQL execution for Databricks with minimal dependencies
• databricks-labs-pylint — Plugin for PyLint to support Databricks specific code patterns and best practices.
• databricks-labs-pytester — Python Testing for Databricks
• databricks-labs-remorph — SQL code converter and data reconcilation tool for accelerating data onboarding to Databricks from EDW, CDW and other ETL sources.
• databricks-labs-ucx — UCX - Unity Catalog Migration Toolkit
• databricks-langchain — Support for Databricks AI support in LangChain
• databricks-rag-studio — Databricks RAG Studio Library
• databricks-rocket — Keep your local python scripts installed and in sync with a databricks notebook. Shortens the feedback loop to develop projects using a hybrid enviroment
• databricks-sqlalchemy-oauth — SQLAlchemy OAuth connector to Databricks
• datacontract-cli — The datacontract CLI is an open source command-line tool for working with Data Contracts. It uses data contract YAML files to lint the data contract, connect to data sources and execute schema and quality tests, detect breaking changes, and export to different formats. The tool is written in Python. It can be used as a standalone CLI tool, in a CI/CD pipeline, or directly as a Python library.
• davidkhala.databricks — no summary
• db-az-sync-provider — A PDM package to sync Azure users, roles and service principals to Databricks
• dbt-databricks — The Databricks adapter plugin for dbt
• dbtunnel — Run app and get cluster proxy url for it in databricks clusters
• dbxio — High-level Databricks client
• dlt-meta — DLT-META Framework
• fabricks — no summary
• featurebyte — Python Library for FeatureOps
• gradiently — no summary
• harlequin-databricks — A Harlequin adapter for Databricks.
• iMapHub — Library created to map two Dataset
• integral_deid — PHI taggging and redaction
• laktory — A DataOps framework for building a lakehouse
• mapGlobaltoLocal — Library created to map two Dataset
• metamart-ingestion — Ingestion Framework for MetaMart
• metaphor-connectors — A collection of Python-based 'connectors' that extract metadata from various sources to ingest into the Metaphor app.
• mlflow-extensions — Extensions for mlflow to make the devloop better for custom models.
• mlrpc — Deploy FastAPI applications on MLFlow
• mlrun — Tracking and config of machine learning runs
• mosaicml — Composer is a PyTorch library that enables you to train neural networks faster, at lower cost, and to higher accuracy.
• mosaicml-streaming — Streaming lets users create PyTorch compatible datasets that can be streamed from cloud-based object stores
• mymaplib-123 — Library created to map two Dataset
• openmetadata-ingestion — Ingestion Framework for OpenMetadata
• pfore-cloud-utilities — Provides utility functions for cloud-based workflows.
• pyjaws — no summary
• pyspark-data-sources — Custom Spark data sources for reading and writing data in Apache Spark, using the Python Data Source API
• quollio-core — Quollio Core
• rtdip-sdk — no summary
• serra — Simplified Data Pipelines
• shipyard-databricks — A local client for connecting and working with Databricks
• shipyard-databricks-sql — A local client for connecting and working Databricks SQL Warehouses
• spark-instructor — A library for building structured LLM responses with Spark
• spetlr — A python ETL libRary (SPETLR) for Databricks powered by Apache SPark.
• spetlr-tools — Supplements to the python SPark ETL libRary (SPETLR) for Databricks.
• tecton-parallel-retrieval — [private preview] Parallel feature retrieval for Tecton
• testlib123 — Library created to map two Dataset
• uc-functions — Decorator to compile Python functions to Databricks UDFs sql statements and inline all the dependencies
• unstructured-cpu — A library that prepares raw documents for downstream ML tasks.
• unstructured-ingest — A library that prepares raw documents for downstream ML tasks.
• zgl-streaming — Streaming lets users create PyTorch compatible datasets that can be streamed from cloud-based object stores
• zipher-sdk — Python SDK for programmatic access to the Zipher API